U.S. DOE Agile BioFoundry: Organization and...

Nathan J. [email protected]

Principal Investigator, DOE Agile BioFoundry

ABF Industry DayEmeryville, CAOctobober 4, 2019

U.S. DOE Agile BioFoundry:Organization and Capabilities

2 | © 2016-2019 Agile BioFoundry

Goal Statement

• Goal: Enable biorefineries to achieve 50% reductions in time to bioprocess scale-up as compared to the current average of around 10 years by establishing a distributed Agile BioFoundry that will productionize synthetic biology.

• Outcomes: 10X improvement in Design-Build-Test-Learn cycle efficiency, new host organisms, new IP and manufacturing technologies effectively translated to U.S. industry ensuring market transformation.

• Relevance: Public infrastructure investment that increases U.S. industrial competitiveness and enables new opportunities for private sector growth and jobs.


Public Infrastructure Investment Enables Private Industry

Public investment in biomanufacturing infrastructure

Private investment in product development, scaling, and tailoring to unique pathways and products

Adapted from Lyft


A Distributed Agile BioFoundry


Molecule X

Molecule Y

Molecule Z

Time and cost for commercialization

~10 years, $100M

~8 years, $50M

~5 years, $25M

Years 1-3 (5 hosts)

Years 4-6 (20 hosts)

Years 7-9 (50 hosts)

Agile BioFoundry Will Reduce Time-to-Scale up


• Task 1: Design-Build-Test-Learn (Nathan Hillson - lead)– Integrate design-build-test-learn cycle with process automation and sample tracking.

• Task 2: Integrated Analysis (Ryan Davis/Thathiana Benavides – co-leads)– Evaluate proposed molecules; develop, update, and improve existing process designs and LCA.

• Task 3: Host Onboarding (Taraka Dale/Adam Guss – co-leads)– Evaluate possible host organisms to determine which on-boarding criteria are not yet met, and

fill these gaps through tool development and data collection.

• Task 4: Process Scale-up (Davinia Salvachua/Deepti Tanjore – co-leads)– Standardize, produce, ship, and store hydrolysates; compare clean sugar processes with

hydrolysates; test and scale fermentation to improve titer, rate, and yield; provide integrated, bench-scale data for TEA and LCA; scale fermentation to produce data for Learn.

• Task 5: Industry Engagement (Emily Scott/Chris Johnson/Phil Laible – co-leads)– Identify barriers to industry adoption of synthetic biology technologies, expand number and

diversity of industry partnerships, and establish a set of metrics for determining impact of project technologies on industry.

• Task 6: Management (Blake Simmons - lead)– Manage project management, develop internal and external communications, provide

deliverables to BETO, and make some capital equipment purchases.

Six Tasks for Overall Project


Subtask 1.1Design

John Gladden (SNL)Gregg Beckham (NREL)

Subtask 1.2Build

Nathan Hillson (LBNL)

Subtask 1.3Test

Jon Magnusson (PNNL)

Subtask 1.4Learn

Phil Laible (ANL)Hector Garcia-Martin (LBNL)

Task 1DBTL

Nathan Hillson (LBNL)

Task 2Integrated Analysis

Ryan Davis (NREL)Thathiana Benavides (ANL)

Task 3Host OnboardingTaraka Dale (LANL)Adam Guss (ORNL)

Task 4Process Integration and Scaling

Davinia Salvachua (NREL)Deepti Tanjore (LBNL)

ExecutiveCommittee Industry PartnershipsIndustry Advisory

Board

Task 6Project Management

and IntegrationAlastair Robinson (LBNL)Blake Simmons (LBNL)

BETO Technology Manager

Jay Fitzgerald

Task 5Industry Engagement and Outreach

Chris Johnson (NREL)Phil Laible (ANL)

Emily Scott (LBNL)

Org Chart


Test

PutativeTargets

Learn

IntegrationScheduler/LIMS

Targets

Target Metrics Achieved

Scale-up:1-1000 LPredictive toolkits

Build

Host On-boarding

Design

TEA/LCA

The Agile BioFoundry Approach


Highlights – DBTL infrastructure

TestLearn

Integration

BuildDesign

EASyExtract

• Lyse the sample (if necessary) in water• Add cold (-20°C) chloroform/methanol (2:1 ,v/v) to

sample in 5:1 ratio over sample volume.

Isolate• Let stand on ice for 5 min, vortex• Centrifuge at 12,000 rpm for 10 min at 4°C

Collect

• Collect the upper layer (metabolites)• Collect the lower layer (lipids)• Dry the protein interlayer

Digest

• Re-solubilize the protein pellet in 8M urea with sonication (add powder urea for typical global digestion)

• BCA assay, add 10mM DTT, incubate 60°C for 30 min• Digest with trypsin• C-18 SPE clean-up

Polar Metabolites

Proteins

Lipids

Transcriptomics,Metabolomics,Proteomics, &

Lipidomics

Biosensors

EDDData QualityAssessment

X !

flux controlcoefficients

Bayesian Inference:Metabolic Kinetics

Kinetic Learning

SequenceValidation

Metabolic Modeling Deep Learning


Highlights – Integrated Analysis

Decreasing GHG emission by using less GHG intensive chemicals

25%

NaOH NH4OH

Example of outlining key drivers in both cost and sustainability

Quantify “economic gradient” of targeting yield or productivity

Key Outcome and Link to R&D:Bounding analysis to show help identify critical R&D targets. ABF adopted 0.5 g/L/hr productivity target.

Key Outcome and Link to R&D:ABF is testing the use of other neutralizing agents to see impact of performance.


Highlights – Host Onboarding

Tier 1Annotated genome; growth conditions; growth kinetics and simple growth models; antibiotic susceptibility; selectable markers; transformation methods; plasmids/vectors; basic expression parts; biosafety/biosecurity information

Tier 2Substrate utilization panel; toxicity profiles; bioreactor growth; counter-selectable markers; genome integration system; chromosomal safe sites/landing pads; induction systems; panel of constitutive promoters, RBSs, terminators; models of promoters and RBSs/Kozak sequences; genome-scale models; pan genome analysis; transcriptomic, proteomic, metabolomic datasets

Tier 3Biosensors; cellular stress monitoring; CRISPR/CAS, Lambda Red, Cre-lox systems;advanced genomic integration platforms; gene expression tuning; high throughout protein engineering platform; lipidomic and glycomic datasets; centralized omics databases; multi-omic data integration and analysis; protein localization; protein degradation tags; protein interactome datasets; 13C-MFA experiments and model; kinetic model; population balance model

Tier 4Culture scalability; saturated deletion/loss of function libraries; genomic overexpression platform; adaptive laboratory evolution/cell sorted libraries; baseline strains for maximal flux to metabolic nodes; cellular state sensors and dynamically regulated production strains; signaling model, gene regulation model, multi-scale model; predictive cellular model

Tier System Criteria - “Hostability”Firmicutes

Cyanobacteria

Fungi AlgaeProteobacteria

ArchaeaActinobacteria

Hostsfatty alcohols

terpenes wax esters

polyhydroxyalkanoates

alkanesfatty acidsTargets

Target/Host PairRanking

Design

Build

Test

Learn

Tier ≥1

Tier <1

HostImprovement

Onboardable

• Tier 1 represents the basic tools needed for DBTL• Hosts that do not meet Tier 1 require further development prior to usage• Tools increase in sophistication as an organism moves up Tiers• Not all tools in all Tiers are required for all organisms


Highlights – Process Integration/Scale-upHydrolysate productionTwo batches to date implementing process improvements at pilot scale

Round Robin study for muconate

Pan-scale muconateTest/Learn

Bioprocess development

05

1015202530

NREL ABPDU

Tite

r (g/

L)

↑20%

0510152025

0

20

40

60

0 24 48 72 96 120 144 168Conc

entra

tion

(g/L

)

OD600

Time (h)


• Revamped ABF website– Capabilities section; template non-negotiable CRADA; 2019 BETO Peer Review slides/posters

Highlights – Industry Outreach


• ABF Annual Meeting: July 30-31, 2019 in Richland, WA

Highlights – Management


FY17 ABF DFO

• Goal: to accelerate innovation and adoption of new biomanufacturingapproaches that will foster growth of the bioeconomy.

• Approach: oversee a $5M directed funding opportunity (DFO) for industry partners to utilize the ABF to develop novel microbial hosts and bioproducts or to develop new capabilities and approaches that will advance all aspects of the Design-Build-Test-Learn biomanufacturing cycle.

• Details: $5M to be made available to the National Labs to collaborate with industrial partners. Projects limited to two years and $500K to $2M total per project.

2017 Timeline:June 21 - RFP live on ABF websiteJuly 24 - Proposals dueJuly 31 – ABF raw scores dueAug 4 – initial selections madeAug 7-10 – BETO internal briefingsAugust 11 - BETO concurrence on final selectionsAugust 14 - Notifications go outAugust 25 - AOPs entered into EERE systemSeptember 1 - Process initiated for $$ sent to labs

Proposal response highlights:19 proposals submitted (18 industry | 1 academic)$19.2M requested (4X oversubscription of resources)Indicates industry is very interested in leveraging ABF

7 Proposals awarded and implemented as CRADAs


FY18 DOE BEEPS FOA: Topic 2 (ABF)


• Approach: competitive DOE FOA process to award funds for financial assistance addressing the development of technologies able to contribute to the production of price-competitive biofuels and bioproducts.

• Details: 0-5 awards in topic area 2 (Agile BioFoundry Industry Partnership Initiative), with a range of $1,000,000-$2,000,000 per award.

2018 Timeline:May 3 – FOA issue dateMay 30 – Letters of intent dueJune 27 – Full applications dueAug 3 – Responses to Reviewers’ comments dueSeptember 4 - BETO announces awardeesSeptember – Award Negotiations underway

Proposal response highlights:Number of “ABF coordination calls” with industry: 22Number of proposals submitted without ABF call: 1Number of letters of intent not encouraged: 2Number of full proposals submitted: 11Indicates industry continues to be very interested in leveraging the ABF.

3 proposals awarded

$2M

$1.3M

$2M


FY19 DOE FOA: Topic 7b (ABF)


• Approach: competitive DOE FOA process to award funds for financial assistance addressing the development of technologies able to contribute to the production of price-competitive biofuels and bioproducts.

2 proposals awarded

$2.5M

$1.8M


• Why these projects and BETO investments are so important– Expand the range of ABF targets and hosts– Stress-test ABF capabilities and identify weaknesses and opportunities– Bring new technologies in to the ABF and opportunities to license ABF technology out– Early stage investments that will be crucial to the ABF accomplishing its overall goal and

its desired outcomes (many relate directly to industry impact and technology transfer)– Ensure that ABF development is responsive to industry– Increase industry exposure (beyond funded companies) to the ABF and its capabilities– Quantitatively demonstrate industry interest in leveraging the ABF

• New for FY19: template ABF CRADA– Publicly accessible from the ABF website: https://agilebiofoundry.org/work-with-us/– Non-negotiable for projects receiving DOE funding– Includes new “Extended Non-Exclusive Option” IP model

Working with Industry: FY17 Direct-Funded Opportunities and FY18-19 FOAs


FY19 Milestones CompletedMilestone (synopsis) Task FY19

QuarterType

Selections of new target molecule & existing molecule in different host

Target/Host Q1 Quarterly (Regular)

4X Build sequence validation capacity increase from FY18 to FY19

DBTL Infrastructure Q2 Quarterly (Regular)

TEA and LCA on new FY19 target molecule Integrated Analysis Q2 Quarterly (Regular)

Deep Learning non-intuitive predictions DBTL Infrastructure Q2 Quarterly (Regular)

Titer goals in range of 1 to 10 g/L Target/Host Q3 Quarterly (Regular)

Transformation in new organism(s) Host Onboarding Q3 Quarterly (Regular)

5X Test capacity increase from FY17 to FY19 DBTL Infrastructure Q3 Quarterly (Regular)

Promoters in new SOT organisms Host Onboarding Q4 Annual (Regular)

10L scale using DMR-EH hydrolysate, with 10 g/L, 100 mg/L/h, 40% yield

Process Integration & Scaling

Q4 Annual (Regular)

SWOT Analysis Industry Engagement & Outreach

Q4 Annual (Regular)

DBTL Activity, Quarterly/Milestone, and final AOP reports sent to BETO. Updates to ABF website

Management Q4 Annual (Regular)

Value of non-intuitive Learn predictions demonstrated

Target/Host Q4 Go/No-Go


• We have a long term strategic vision for the ABF

• Our future work will focus on the technical and operational barriers to achieving the overall ABF goal and its desired outcomes

• Some challenges facing the ABF:– Show Learn can add value through non-intuitive predictions– Demonstrate industry-relevant ABF competencies across targets and hosts– Onboard new hosts and develop tools for them– Increase DBTL cycle capacities and efficiencies; reduce cycle time– Keep current strength / weakness / opportunities / threat (SWOT) assessments– Demonstrate reproducible geographically distributed unit operations– Find sustainable ABF IP / licensing / contracting model(s)– Demonstrate that past work and Learnings increase the efficiency of new work

• Next slides show our current FY19 and pending FY20-22 milestones

How we are thinking about our future work


• FY20 Annual Smart– Reproducibility of 3 distributed Test unit operations, including bioreactor scale-

up, quantified through comparison of results post data quality assurance for on-site vs. off-site sample analysis. Identify 3 or more variables that capture unit operation variability; reproducibility will be determined by less than 10% variability in these variables at the distributed Test sites.

• Go/No-Go Decision, Q2 FY21– 5 target molecules or tools transferred between host organisms. Successful

target molecule transfers will have product titers greater than the lesser of 1 g/L or the titer established in the prior host organism at time of transfer. For 3 of 5 of these, 2X biological engineering cycle efficiency gains demonstrated over attempts made in prior host organisms

• FY22 Annual Smart– 5X efficiency (cycle time, how many cycles, how many strains per cycle, per

person/ instrument/ resource) improvement in DBTL engineering cycle compared to FY19 baseline efficiency demonstrated

– Bring a total 20 microbial hosts (20 species) to at least Tier 1, and provide corresponding information, resources, and tools via publicly-accessible ABF website

Representative FY20-22 Milestones


Summary

• Goal: Enable biorefineries to achieve 50% reductions in time to bioprocess scale-up as compared to the current average of around 10 years by establishing a distributed Agile BioFoundry that will productionize synthetic biology.

• Outcomes: 10X improvement in Design-Build-Test-Learn cycle efficiency, new host organisms, new IP and manufacturing technologies effectively translated to U.S. industry ensuring market transformation.

• Relevance: Public infrastructure investment that increases U.S. industrial competitiveness and enables new opportunities for private sector growth and jobs.

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U.S. DOE Agile BioFoundry: Organization and...

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